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Nonlinear optimal control is vital for numerous applications but remains challenging for unknown systems due to the difficulties in accurately modelling dynamics and handling computational demands, particularly in high-dimensional settings.…

Systems and Control · Electrical Eng. & Systems 2024-12-03 Zhexuan Zeng , Ruikun Zhou , Yiming Meng , Jun Liu

The aim of the present paper is to study the existence, uniqueness and some other properties of solutions of a certain partial dynamic integrodifferential equations. The Banach fixed point theorem and certain fundamental inequality with…

Dynamical Systems · Mathematics 2016-05-03 Deepak B. Pachpatte

We prove weighted estimates for singular integral operators which operate on function spaces on a half-line. The class of admissible weights includes Muckenhoupt weights and weights satisfying Sawyer's one-sided conditions. The kernels of…

Classical Analysis and ODEs · Mathematics 2014-10-15 Ralph Chill , Sebastian Krol

The explicit split-operator algorithm is often used for solving the linear and nonlinear time-dependent Schr\"{o}dinger equations. However, when applied to certain nonlinear time-dependent Schr\"{o}dinger equations, this algorithm loses…

Chemical Physics · Physics 2024-09-26 Julien Roulet , Jiří Vaníček

In the paper, we investigate weighted composition operators on Bergman spaces of a half-plane. We characterize weighted composition operators which are hermitian and those which are complex symmetric with respect to a family of…

Functional Analysis · Mathematics 2021-11-30 Pham Viet Hai , Osmar R. Severiano

We study an inverse problem for variable coefficient fractional parabolic operators of the form $(\partial_t -\operatorname{div}(A(x) \nabla_x)^s + q(x,t)$ for $s\in(0,1)$ and show the unique recovery of $q$ from exterior measured data.…

Analysis of PDEs · Mathematics 2023-07-04 Agnid Banerjee , Soumen Senapati

We give a simple algebraic derivation of a useful determinantal identity for multilevel systems such as random matrix chains and finite determinantal point processes, with applications to the calculation of point correlators, gap…

Mathematical Physics · Physics 2014-10-07 J. Harnad , A. Yu. Orlov

We study strictly parabolic stochastic partial differential equations on $\R^d$, $d\ge 1$, driven by a Gaussian noise white in time and coloured in space. Assuming that the coefficients of the differential operator are random, we give…

Probability · Mathematics 2007-05-23 Marco Ferrante , Marta Sanz-Solé

The purpose of the paper is to establish weighted maximal $L_p$-inequalities in the context of operator-valued martingales on semifinite von Neumann algebras. The main emphasis is put on the optimal dependence of the $L_p$ constants on the…

Operator Algebras · Mathematics 2022-11-18 Tomasz Gałązka , Yong Jiao , Adam Osękowski , Lian Wu

The weighted star-discrepancy has been introduced by Sloan and Wo{\'z}niakowski to reflect the fact that in multidimensional integration problems some coordinates of a function may be more important than others. It provides upper bounds for…

Numerical Analysis · Mathematics 2013-12-06 Christoph Aistleitner

We study function-valued solutions of a class of stochastic partial differential equations, involving operators with polynomially bounded coefficients. We consider semilinear equations under suitable parabolicity hypotheses. We provide…

Probability · Mathematics 2022-06-16 Alessia Ascanelli , Sandro Coriasco , André Suß

We prove a new general differential identity and an associated integral identity, which entails a pair of solutions of the Poisson equation with constant source term. This generalizes a formula that the first and third authors previously…

Analysis of PDEs · Mathematics 2024-05-16 Rolando Magnanini , Riccardo Molinarolo , Giorgio Poggesi

We first state a special type of It\^o formula involving stochastic integrals of both standard and fractional Brownian motions. Then we use Doss-Sussman transformation to establish the link between backward doubly stochastic differential…

Probability · Mathematics 2011-03-18 Shuai Jing

This paper is concerned with computations of a few smaller eigenvalues (in absolute value) of a large extremely ill-conditioned matrix. It is shown that smaller eigenvalues can be accurately computed for a diagonally dominant matrix or a…

Numerical Analysis · Mathematics 2017-05-16 Qiang Ye

We analyze a varying-coefficient dynamic spatial autoregressive model with spatial fixed effects. One salient feature of the model is the incorporation of multiple spatial weight matrices through their linear combinations with varying…

Methodology · Statistics 2025-05-12 Zetai Cen , Yudong Chen , Clifford Lam

Eigenvalues in the essential spectrum of a weighted Sturm-Liouville operator are studied under the assumption that the weight function has one turning point. An abstract approach to the problem is given via a functional model for indefinite…

Spectral Theory · Mathematics 2012-03-06 I. M. Karabash

The increasing availability of experimental data has intensified interest in calibrating stochastic models, raising fundamental questions about parameter identifiability. Structural identifiability determines whether parameters can be…

Methodology · Statistics 2026-05-14 Arianna Ceccarelli , Alexander P. Browning , Ruth E. Baker

In this paper, we study large and moderate deviation principles for stochastic partial differential equations (SPDEs) on metric graphs and their associated multiscale models via the weak convergence approach, providing a refined…

Probability · Mathematics 2025-09-09 Jianbo Cui , Derui Sheng

In this paper, we establish the Carleman estimates for forward and backward stochastic fourth order Schr\"{o}dinger equations, on basis of which, we can obtain the observability, unique continuation property and the exact controllability…

Optimization and Control · Mathematics 2017-03-13 Peng Gao

An old problem in multivariate statistics is that linear Gaussian models are often unidentifiable, i.e. some parameters cannot be uniquely estimated. In factor (component) analysis, an orthogonal rotation of the factors is unidentifiable,…

Machine Learning · Statistics 2023-05-04 Aapo Hyvärinen , Ilyes Khemakhem , Ricardo Monti
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